""" Copyright (C) 2018-2020 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import unittest import numpy as np from mo.front.common.partial_infer.utils import int64_array from mo.graph.graph import Node from mo.ops.crop import Crop from mo.utils.unittest.graph import build_graph class TestCropPartialInfer(unittest.TestCase): @staticmethod def _create_graph_type1(): nodes_attributes = {'crop_input': {'shape': None, 'value': None, 'kind': 'data'}, 'crop_node': {'type': 'Crop', 'kind': 'op'}, 'crop_output': {'shape': None, 'value': None, 'kind': 'data'} } return build_graph(nodes_attributes, [ ('crop_input', 'crop_node'), ('crop_node', 'crop_output') ], { 'crop_input': {'shape': int64_array([1, 3, 224, 224])}, 'crop_node': {'axis': int64_array([2, 3]), 'crop_begin': int64_array([10, 15]), 'crop_end': int64_array([10, 15]) }, }) @staticmethod def _create_graph_type2(): nodes_attributes = {'crop_input': {'shape': None, 'value': None, 'kind': 'data'}, 'crop_node': {'type': 'Crop', 'kind': 'op'}, 'crop_output': {'shape': None, 'value': None, 'kind': 'data'} } return build_graph(nodes_attributes, [ ('crop_input', 'crop_node'), ('crop_node', 'crop_output') ], { 'crop_input': {'shape': int64_array([1, 3, 224, 224])}, 'crop_node': {'axis': int64_array([2, 3]), 'dim': int64_array([100, 150])}, }) @staticmethod def _create_graph_type3(): nodes_attributes = {'crop_input': {'shape': None, 'value': None, 'kind': 'data'}, 'crop_input2': {'shape': None, 'value': None, 'kind': 'data'}, 'crop_node': {'type': 'Crop', 'kind': 'op'}, 'crop_output': {'shape': None, 'value': None, 'kind': 'data'} } return build_graph(nodes_attributes, [ ('crop_input', 'crop_node'), ('crop_input2', 'crop_node'), ('crop_node', 'crop_output') ], { 'crop_input': {'shape': int64_array([1, 3, 224, 224])}, 'crop_input2': {'shape': int64_array([1, 3, 100, 150])}, 'crop_node': {'axis': 2, 'offset': int64_array([10, 15])}, }) def test_crop_type1_infer(self): graph = self._create_graph_type1() crop_node = Node(graph, 'crop_node') Crop.infer(crop_node) exp_shape = int64_array([1, 3, 204, 194]) res_shape = graph.node['crop_output']['shape'] self.assertTrue(np.array_equal(exp_shape, res_shape), 'shapes do not match expected: {} and given: {}'.format(exp_shape, res_shape)) def test_crop_type1_infer_neg1(self): graph = self._create_graph_type1() crop_node = Node(graph, 'crop_node') crop_node['axis'] = None Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type1_infer_neg2(self): graph = self._create_graph_type1() crop_node = Node(graph, 'crop_node') crop_node['crop_begin'] = int64_array([1, 2, 3]) Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type2_infer(self): graph = self._create_graph_type2() crop_node = Node(graph, 'crop_node') Crop.infer(crop_node) exp_shape = int64_array([1, 3, 100, 150]) res_shape = graph.node['crop_output']['shape'] self.assertTrue(np.array_equal(exp_shape, res_shape), 'shapes do not match expected: {} and given: {}'.format(exp_shape, res_shape)) def test_crop_type2_infer_neg1(self): graph = self._create_graph_type2() crop_node = Node(graph, 'crop_node') crop_node['dim'] = int64_array([1, 2, 3]) Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type2_infer_neg2(self): graph = self._create_graph_type2() crop_node = Node(graph, 'crop_node') crop_node['dim'] = None crop_node['crop_begin'] = None Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type3_infer(self): graph = self._create_graph_type3() crop_node = Node(graph, 'crop_node') Crop.infer(crop_node) exp_shape = int64_array([1, 3, 100, 150]) res_shape = graph.node['crop_output']['shape'] self.assertTrue(np.array_equal(exp_shape, res_shape), 'shapes do not match expected: {} and given: {}'.format(exp_shape, res_shape)) def test_crop_type3_infer_neg1(self): graph = self._create_graph_type3() crop_node = Node(graph, 'crop_node') crop_input2 = Node(graph, 'crop_input2') crop_input2.shape = None Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type3_infer_neg2(self): graph = self._create_graph_type3() crop_node = Node(graph, 'crop_node') crop_node['axis'] = None Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type3_infer_neg3(self): graph = self._create_graph_type3() crop_node = Node(graph, 'crop_node') crop_node['offset'] = None Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape) def test_crop_type3_infer_neg4(self): graph = self._create_graph_type3() crop_node = Node(graph, 'crop_node') crop_input2 = Node(graph, 'crop_input2') crop_input2.shape = int64_array([1, 4, 423, 563]) Crop.infer(crop_node) self.assertIsNone(crop_node.out_node().shape)